Showing papers by "Ying Hu published in 2015"

Butyrylated starch intake can prevent red meat-induced O6-methyl-2-deoxyguanosine adducts in human rectal tissue: a randomised clinical trial

Abstract: Epidemiological studies have identified increased colorectal cancer (CRC) risk with high red meat (HRM) intakes, whereas dietary fibre intake appears to be protective. In the present study, we examined whether a HRM diet increased rectal O6-methyl-2-deoxyguanosine (O6MeG) adduct levels in healthy human subjects, and whether butyrylated high-amylose maize starch (HAMSB) was protective. A group of twenty-three individuals consumed 300 g/d of cooked red meat without (HRM diet) or with 40 g/d of HAMSB (HRM+HAMSB diet) over 4-week periods separated by a 4-week washout in a randomised cross-over design. Stool and rectal biopsy samples were collected for biochemical, microbial and immunohistochemical analyses at baseline and at the end of each 4-week intervention period. The HRM diet increased rectal O6MeG adducts relative to its baseline by 21 % (P< 0·01), whereas the addition of HAMSB to the HRM diet prevented this increase. Epithelial proliferation increased with both the HRM (P< 0·001) and HRM+HAMSB (P< 0·05) diets when compared with their respective baseline levels, but was lower following the HRM+HAMSB diet compared with the HRM diet (P< 0·05). Relative to its baseline, the HRM+HAMSB diet increased the excretion of SCFA by over 20 % (P< 0·05) and increased the absolute abundances of the Clostridium coccoides group (P< 0·05), the Clostridium leptum group (P< 0·05), Lactobacillus spp. (P< 0·01), Parabacteroides distasonis (P< 0·001) and Ruminococcus bromii (P< 0·05), but lowered Ruminococcus torques (P< 0·05) and the proportions of Ruminococcus gnavus, Ruminococcus torques and Escherichia coli (P< 0·01). HRM consumption could increase the risk of CRC through increased formation of colorectal epithelial O6MeG adducts. HAMSB consumption prevented red meat-induced adduct formation, which may be associated with increased stool SCFA levels and/or changes in the microbiota composition.

GNL3 and SKA3 are novel prostate cancer metastasis susceptibility genes.

Abstract: Prostate cancer (PC) is very common in developed countries. However, the molecular determinants of PC metastasis are unclear. Previously, we reported that germline variation influences metastasis in the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of PC. These mice develop prostate tumors similar to a subset of poor outcome, treatment-associated human PC tumors. Here, we used TRAMP mice to nominate candidate genes and validate their role in aggressive human PC in PC datasets and cell lines. Candidate metastasis susceptibility genes were identified through quantitative trait locus (QTL) mapping in 201 (TRAMP × PWK/PhJ) F2 males. Two metastasis-associated QTLs were identified; one on chromosome 12 (LOD = 5.86), and one on chromosome 14 (LOD = 4.41). Correlation analysis using microarray data from (TRAMP × PWK/PhJ) F2 prostate tumors identified 35 metastasis-associated transcripts within the two loci. The role of these genes in susceptibility to aggressive human PC was determined through in silico analysis using multiple datasets. First, analysis of candidate gene expression in two human PC datasets demonstrated that five candidate genes were associated with an increased risk of aggressive disease and lower disease-free survival. Second, four of these genes (GNL3, MAT1A, SKA3, and ZMYM5) harbored SNPs associated with aggressive tumorigenesis in the PLCO/CGEMS GWAS of 1172 PC patients. Finally, over-expression of GNL3 and SKA3 in the PC-3 human PC cell line decreased in vitro cell migration and invasion. This novel approach demonstrates how mouse models can be used to identify metastasis susceptibility genes, and gives new insight into the molecular mechanisms of fatal PC.

Generating a focused view of disease ontology cancer terms for pan-cancer data integration and analysis.

Abstract: Bio-ontologies provide terminologies for the scientific community to describe biomedical entities in a standardized manner. There are multiple initiatives that are developing biomedical terminologies for the purpose of providing better annotation, data integration and mining capabilities. Terminology resources devised for multiple purposes inherently diverge in content and structure. A major issue of biomedical data integration is the development of overlapping terms, ambiguous classifications and inconsistencies represented across databases and publications. The disease ontology (DO) was developed over the past decade to address data integration, standardization and annotation issues for human disease data. We have established a DO cancer project to be a focused view of cancer terms within the DO. The DO cancer project mapped 386 cancer terms from the Catalogue of Somatic Mutations in Cancer (COSMIC), The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, Therapeutically Applicable Research to Generate Effective Treatments, Integrative Oncogenomics and the Early Detection Research Network into a cohesive set of 187 DO terms represented by 63 top-level DO cancer terms. For example, the COSMIC term ‘kidney, NS, carcinoma, clear_cell_renal_cell_carcinoma’ and TCGA term ‘Kidney renal clear cell carcinoma’ were both grouped to the term ‘Disease Ontology Identification (DOID):4467 / renal clear cell carcinoma’ which was mapped to the TopNodes_DOcancerslim term ‘DOID:263 / kidney cancer’. Mapping of diverse cancer terms to DO and the use of top level terms (DO slims) will enable pan-cancer analysis across datasets generated from any of the cancer term sources where pan-cancer means including or relating to all or multiple types of cancer. The terms can be browsed from the DO web site (http://www.disease-ontology.org) and downloaded from the DO’s Apache Subversion or GitHub repositories. Database URL: http://www.disease-ontology.org

TCF21 hypermethylation in genetically quiescent clear cell sarcoma of the kidney

Abstract: // Saskia L Gooskens 1,2 , Samantha Gadd 3 , Jaime M Guidry Auvil 4 , Daniela S Gerhard 4 , Javed Khan 5 , Rajesh Patidar 5 , Daoud Meerzaman 6 , Qing-Rong Chen 6 , Chih Hao Hsu 6 , Chunhua Yan 6 , Cu Nguyen 6 , Ying Hu 6 , Charles G Mullighan 7 , Jing Ma 7 , Lawrence J Jennings 3 , Ronald R de Krijger 8,9 , Marry M van den Heuvel-Eibrink 2 , Malcolm A Smith 10 , Nicole Ross 11 , Julie M Gastier-Foster 11 and Elizabeth J Perlman 3 1 Department of Pediatric Hematology and Oncology, Erasmus MC - Sophia Children’s Hospital, Rotterdam, The Netherlands 2 Department of Pediatric Oncology, Princess Maxima Center for Pediatric Oncology, Utrecht, The Netherlands 3 Department of Pathology, Ann and Robert H Lurie Children’s Hospital of Chicago, Northwestern University’s Feinberg School of Medicine and Robert H Lurie Cancer Center, Chicago, IL, USA 4 Office of Cancer Genomics, National Cancer Institute, Bethesda, MD, USA 5 Genetics Branch, Oncogenomics section, National Cancer Institute, Bethesda, MD, USA 6 Computational Genomics Research Group, Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA 7 Department of Pathology, St Jude Children’s Research Hospital, Memphis, TN, USA 8 Department of Pathology, Josephine Nefkens Institute, Erasmus MC, Rotterdam, The Netherlands 9 Department of Pathology, Reinier de Graaf Hospital, Delft, The Netherlands 10 Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD, USA 11 Department of Pathology and Laboratory Medicine, Nationwide Children’s Hospital, Ohio State University College of Medicine, Columbus, OH, USA Correspondence to: Elizabeth J Perlman, email: // Keywords : clear cell sarcoma of the kidney, whole genome sequencing, methylation, TCF21, TARID Received : April 10, 2015 Accepted : June 07, 2015 Published : June 28, 2015 Abstract Clear Cell Sarcoma of the Kidney (CCSK) is a rare childhood tumor whose molecular pathogenesis remains poorly understood We analyzed a discovery set of 13 CCSKs for changes in chromosome copy number, mutations, rearrangements, global gene expression and global DNA methylation No recurrent segmental chromosomal copy number changes or somatic variants (single nucleotide or small insertion/deletion) were identified One tumor with t(10;17)(q22;p13) involving fusion of YHWAE with NUTM2B was identified Integrated analysis of expression and methylation data identified promoter hypermethylation and low expression of the tumor suppressor gene TCF21 ( Pod-1/capsulin/epicardin) in all CCSKs except the case with t(10;17)(q22;p13) TARID , the long noncoding RNA responsible for demethylating TCF21 , was virtually undetectable in most CCSKs TCF21 hypermethylation and decreased TARID expression were validated in an independent set of CCSK tumor samples The presence of significant hypermethylation of TCF21, a transcription factor known to be active early in renal development, supports the hypothesis that hypermethylation of TCF21 and/or decreased TARID expression lies within the pathogenic pathway of most CCSKs Future studies are needed to functionally verify a tumorigenic role of TCF21 down-regulation and to tie this to the unique gene expression pattern of CCSK

Necdin is a breast cancer metastasis suppressor that regulates the transcription of c-Myc

Abstract: Metastasis is the primary cause of death in breast cancer. Earlier studies using a mammary tumorigenesis mouse model identified Necdin (Ndn)as a germline modifier of metastasis. Differential expression of Ndn induces a gene-expression signature that predicts prognosis in human breast cancer. Additionally, a non-synonymous germline single nucleotide polymorphism (T50C; V17A) in Ndn distinguishes mouse strains with differing metastatic capacities. To better understand how hereditary factors influence metastasis in breast cancer, we characterized NDN-mediated transcription. Haplotype analysis in a well-characterized breast cancer cohort revealed that NDN germline variation is associated with both NDN expression levels and patient outcome. To examine the role of NDN in mammary tumor metastasis and transcriptional regulation, mouse mammary tumor cell lines stably over-expressing either the wildtype 50T or variant 50C Ndn allele were generated. Cells over-expressing Ndn 50T, but not Ndn 50C, exhibited significant decrease in cell invasiveness and pulmonary metastases compared to control cells. Transcriptome analyses identified a 71-gene expression signature that distinguishes cells over-expressing the two Ndn allelic variants. Furthermore, ChIP assays revealed c-Myc, a target gene of NDN, to be differentially regulated by the allelic variants. These data demonstrate that NDN and the T50C allele regulate gene expression and metastasis efficiency.

Transcriptome Profiling of Pediatric Core Binding Factor AML.

Abstract: The t(8;21) and Inv(16) translocations disrupt the normal function of core binding factors alpha (CBFA) and beta (CBFB), respectively. These translocations represent two of the most common genomic abnormalities in acute myeloid leukemia (AML) patients, occurring in approximately 25% pediatric and 15% of adult with this malignancy. Both translocations are associated with favorable clinical outcomes after intensive chemotherapy, and given the perceived mechanistic similarities, patients with these translocations are frequently referred to as having CBF-AML. It remains uncertain as to whether, collectively, these translocations are mechanistically the same or impact different pathways in subtle ways that have both biological and clinical significance. Therefore, we used transcriptome sequencing (RNA-seq) to investigate the similarities and differences in genes and pathways between these subtypes of pediatric AMLs. Diagnostic RNA from patients with t(8;21) (N = 17), Inv(16) (N = 14), and normal karyotype (NK, N = 33) were subjected to RNA-seq. Analyses compared the transcriptomes across these three cytogenetic subtypes, using the NK cohort as the control. A total of 1291 genes in t(8;21) and 474 genes in Inv(16) were differentially expressed relative to the NK controls, with 198 genes differentially expressed in both subtypes. The majority of these genes (175/198; binomial test p-value < 10(-30)) are consistent in expression changes among the two subtypes suggesting the expression profiles are more similar between the CBF cohorts than in the NK cohort. Our analysis also revealed alternative splicing events (ASEs) differentially expressed across subtypes, with 337 t(8;21)-specific and 407 Inv(16)-specific ASEs detected, the majority of which were acetylated proteins (p = 1.5 x 10(-51) and p = 1.8 x 10(-54) for the two subsets). In addition to known fusions, we identified and verified 16 de novo fusions in 43 patients, including three fusions involving NUP98 in six patients. Clustering of differentially expressed genes indicated that the homeobox (HOX) gene family, including two transcription factors (MEIS1 and NKX2-3) were down-regulated in CBF compared to NK samples. This finding supports existing data that the dysregulation of HOX genes play a central role in biology CBF-AML hematopoiesis. These data provide comprehensive transcriptome profiling of CBF-AML and delineate genes and pathways that are differentially expressed, providing insights into the shared biology as well as differences in the two CBF subsets.

Role of Red Meat and Resistant Starch in Promutagenic Adduct Formation, MGMT Repair, Thymic Lymphoma and Intestinal Tumourigenesis in Msh2 -Deficient Mice.

Abstract: Red meat may increase promutagenic lesions in the colon Resistant starch (RS) can reduce these lesions and chemically induced colon tumours in rodents Msh2 is a mismatch repair (MMR) protein, recognising unrepaired promutagenic adducts for removal We determined if red meat and/or RS modulated DNA adducts or oncogenesis in Msh2-deficient mice A total of 100 Msh2-/- and 60 wild-type mice consumed 1 of 4 diets for 6 months: control, RS, red meat and red meat+RS Survival time, aberrant crypt foci (ACF), colon and small intestinal tumours, lymphoma, colonic O6-methyl-2-deoxyguanosine (O6MeG) adducts, methylguanine methyltransferase (MGMT) and cell proliferation were examined In Msh2-/- mice, red meat enhanced survival compared to control (p<001) and lowered total tumour burden compared to RS (p<0167) Msh2-/- mice had more ACF than wild-type mice (p<0014), but no colon tumours developed Msh2-/- increased cell proliferation (p<0001), lowered DNA O6MeG adducts (p<0143) and enhanced MGMT protein levels (p<0001) compared to wild-type mice, with RS supplementation also protecting against DNA adducts (p<001) No link between red meat-induced promutagenic adducts and risk for colorectal cancer was observed after 6 months' feeding Colonic epithelial changes after red meat and RS consumption with MMR deficiency will differ from normal epithelial cells

Alview: Portable Software for Viewing Sequence Reads in BAM Formatted Files.

Abstract: The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview. The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview.

Abstract 2261: DLGAP5, MAT1A, SKA3, and ZMYM5 are novel susceptibility genes for aggressive prostate cancer

Abstract: Prostate cancer is a common disease with approximately 233,000 men estimated to be diagnosed in the United States alone in 2014. Yet, it is usually an indolent disease with only 13% of patients succumbing to prostate cancer, and the molecular determinants of aggressive prostate cancer remain unclear. Previously, we reported that germline variation influences disease aggressiveness in the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model. These mice develop neuroendocrine prostate tumors similar to a subset of human prostate tumors associated with poor outcomes. Here, we used a multifaceted approach to identify candidate genes for susceptibility to aggressive prostate tumorigenesis and metastasis using the TRAMP mouse model. Candidate prostate cancer metastasis susceptibility genes were identified through quantitative trait locus (QTL) mapping in 201 (TRAMP x PWK/PhJ) F2 males. Two aggressive disease QTLs were identified; one for lymph node metastasis burden on chromosome 12 (LOD = 5.86) and one for distant metastasis-free survival on chromosome 14 (LOD = 4.41). Correlation analysis using microarray data derived from 27 (TRAMP x PWK/PhJ) F2 prostate tumors identified 35 metastasis-associated transcripts within the two loci. The role of these genes in susceptibility to aggressive human prostate cancer was analyzed in two different datasets. First, logistic regression and survival analyses in human prostate cancer gene expression datasets demonstrated that the expression levels of 5 of the 35 candidate genes was associated with both an increased risk of aggressive disease and a poorer disease-free survival. Second, four of these genes - DLGAP5, MAT1A, SKA3, and ZMYM5 - harbored SNPs associated with aggressive tumorigenesis in the PLCO/CGEMS GWAS cohort of 1,172 prostate cancer patients. This approach, novel to the prostate cancer field, demonstrates how mouse models can be used to identify aggressive disease susceptibility genes, and gives new insight into the molecular mechanisms of aggressive disease. Citation Format: Minnkyong Lee, Kendra A. Williams, Ying Hu, Jonathan Andreas, Shashankkumar J. Patel, Suiyuan Zhang, Nigel PS Crawford. DLGAP5, MAT1A, SKA3, and ZMYM5 are novel susceptibility genes for aggressive prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2261. doi:10.1158/1538-7445.AM2015-2261